ArticleFrontiers in plant science2025
GrapeUL-YOLO: bidirectional cross-scale fusion with elliptical anchors for robust grape detection in orchards.
Article in Frontiers in plant science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Research on surface crack segmentation and quantitative degradation assessment in alpine meadows based on UAV imagery and the YOLO-AMSC model.Frontiers in plant science · 2026Article
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Abstract
Accurate grape detection in orchards is a core link in realizing automated harvesting. To address the challenges in orchard environments, such as complex grape backgrounds, variable lighting conditions, and dense occlusion of fruits, this study proposes a highly robust real-time grape detection model for orchard scenarios, namely Grapevine Ultra-Lightweight YOLO (GrapeUL-YOLO). Based on YOLOv11, this model enhances detection performance through three innovative designs: firstly, it adopts a Cross-Scale Residual Feature Backbone (CSRB) as the feature extraction network, combining
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